Automated generation of radical species in crystalline carbohydrate using ab initio MD simulations

Literature Information

Publication Date 2014-06-27
DOI 10.1039/C4CP02179G
Impact Factor 3.676
Authors

Siv G. Aalbergsjø, Ewald Pauwels, Andy Van Yperen-De Deyne, Veronique Van Speybroeck, Einar Sagstuen


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Abstract

As the chemical structures of radiation damaged molecules may differ greatly from their undamaged counterparts, investigation and description of radiation damaged structures is commonly biased by the researcher. Radical formation from ionizing radiation in crystalline α-L-rhamnose monohydrate has been investigated using a new method where the selection of radical structures is unbiased by the researcher. The method is based on using ab initio molecular dynamics (MD) studies to investigate how ionization damage can form, change and move. Diversity in the radical production is gained by using different points on the potential energy surface of the intact crystal as starting points for the ionizations and letting the initial velocities of the nuclei after ionization be generated randomly. 160 ab initio MD runs produced 12 unique radical structures for investigation. Out of these, 7 of the potential products have never previously been discussed, and 3 products are found to match with radicals previously observed by electron magnetic resonance experiments.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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